from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 54.523898 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 23.426407 |
| KNeighborsClassifier_kd_tree | 0.0 | 7.0 | 11.239496 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 48.623110 |
| KMeans | 0.0 | 8.0 | 31.217493 |
| daal4py_KMeans | 0.0 | 5.0 | 34.979661 |
| LogisticRegression | 0.0 | 1.0 | 4.133832 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 55.390518 |
| Ridge | 0.0 | 0.0 | 0.995361 |
| daal4py_Ridge | 0.0 | 0.0 | 0.664602 |
| total | 0.0 | 42.0 | 25.261941 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.142 | 0.009 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.480 | 0.001 | 0.297 | 0.004 | See |
| 1 | KNeighborsClassifier | predict | 0.166 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 0.084 | 0.001 | 1.981 | 0.011 | See |
| 2 | KNeighborsClassifier | predict | 26.292 | 0.339 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 2.030 | 0.044 | 12.952 | 0.001 | See |
| 3 | KNeighborsClassifier | fit | 0.135 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.480 | 0.003 | 0.281 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.163 | 0.015 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.085 | 0.003 | 1.914 | 0.010 | See |
| 5 | KNeighborsClassifier | predict | 35.994 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 2.013 | 0.045 | 17.884 | 0.000 | See |
| 6 | KNeighborsClassifier | fit | 0.121 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.475 | 0.002 | 0.256 | 0.000 | See |
| 7 | KNeighborsClassifier | predict | 0.167 | 0.016 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.083 | 0.001 | 2.025 | 0.009 | See |
| 8 | KNeighborsClassifier | predict | 36.445 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 2.071 | 0.021 | 17.597 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.120 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.477 | 0.003 | 0.252 | 0.000 | See |
| 10 | KNeighborsClassifier | predict | 0.175 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 0.083 | 0.002 | 2.102 | 0.000 | See |
| 11 | KNeighborsClassifier | predict | 13.244 | 0.086 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 2.016 | 0.041 | 6.569 | 0.000 | See |
| 12 | KNeighborsClassifier | fit | 0.121 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.477 | 0.001 | 0.254 | 0.000 | See |
| 13 | KNeighborsClassifier | predict | 0.179 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.081 | 0.000 | 2.200 | 0.000 | See |
| 14 | KNeighborsClassifier | predict | 24.593 | 0.066 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 1.979 | 0.018 | 12.430 | 0.000 | See |
| 15 | KNeighborsClassifier | fit | 0.135 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.477 | 0.001 | 0.283 | 0.000 | See |
| 16 | KNeighborsClassifier | predict | 0.178 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.086 | 0.004 | 2.068 | 0.003 | See |
| 17 | KNeighborsClassifier | predict | 24.629 | 0.067 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 2.052 | 0.028 | 12.003 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.058 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.109 | 0.004 | 0.535 | 0.001 | See |
| 19 | KNeighborsClassifier | predict | 0.019 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.006 | 0.000 | 3.184 | 0.008 | See |
| 20 | KNeighborsClassifier | predict | 22.271 | 0.127 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.309 | 0.004 | 72.150 | 0.000 | See |
| 21 | KNeighborsClassifier | fit | 0.063 | 0.004 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.110 | 0.004 | 0.576 | 0.004 | See |
| 22 | KNeighborsClassifier | predict | 0.025 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.006 | 0.001 | 4.089 | 0.032 | See |
| 23 | KNeighborsClassifier | predict | 32.896 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.315 | 0.006 | 104.508 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.061 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.108 | 0.002 | 0.567 | 0.003 | See |
| 25 | KNeighborsClassifier | predict | 0.024 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 3.787 | 0.050 | See |
| 26 | KNeighborsClassifier | predict | 32.215 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.363 | 0.005 | 88.840 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.060 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.108 | 0.003 | 0.553 | 0.002 | See |
| 28 | KNeighborsClassifier | predict | 0.016 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.006 | 0.000 | 2.585 | 0.008 | See |
| 29 | KNeighborsClassifier | predict | 10.578 | 0.215 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.306 | 0.004 | 34.568 | 0.001 | See |
| 30 | KNeighborsClassifier | fit | 0.059 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.108 | 0.002 | 0.547 | 0.001 | See |
| 31 | KNeighborsClassifier | predict | 0.018 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.006 | 0.001 | 2.880 | 0.015 | See |
| 32 | KNeighborsClassifier | predict | 21.320 | 0.601 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.313 | 0.007 | 68.217 | 0.001 | See |
| 33 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.107 | 0.004 | 0.553 | 0.001 | See |
| 34 | KNeighborsClassifier | predict | 0.018 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 2.833 | 0.008 | See |
| 35 | KNeighborsClassifier | predict | 20.717 | 0.008 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.367 | 0.007 | 56.501 | 0.000 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.104 | 0.052 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.766 | 0.020 | 4.052 | 0.001 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.530 | 0.164 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.481 | 0.007 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.110 | 0.005 | 4.391 | 0.003 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.248 | 0.136 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.806 | 0.017 | 4.030 | 0.002 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 4.365 | 0.268 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.841 | 0.007 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.195 | 0.008 | 4.303 | 0.002 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.235 | 0.110 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.746 | 0.010 | 4.334 | 0.001 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.002 | 0.001 | 2.726 | 0.166 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.988 | 0.057 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.580 | 0.004 | 5.153 | 0.000 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.148 | 0.029 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.779 | 0.009 | 4.040 | 0.000 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 1.612 | 0.359 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.775 | 0.005 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.104 | 0.002 | 7.457 | 0.000 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.196 | 0.040 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.752 | 0.003 | 4.250 | 0.000 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 1.563 | 0.241 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.473 | 0.017 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.188 | 0.002 | 7.824 | 0.000 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.115 | 0.071 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.781 | 0.008 | 3.991 | 0.001 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.002 | 0.001 | 1.349 | 0.140 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.982 | 0.056 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.580 | 0.015 | 8.588 | 0.001 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.532 | 0.020 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.522 | 0.007 | 2.932 | 0.000 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 16.015 | 0.842 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.031 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 32.979 | 0.169 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.548 | 0.029 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.542 | 0.022 | 2.857 | 0.002 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 16.152 | 0.646 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.033 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.001 | 24.261 | 0.150 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.465 | 0.012 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.544 | 0.013 | 2.690 | 0.001 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 16.820 | 0.583 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.051 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.002 | 6.127 | 0.052 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.500 | 0.020 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.546 | 0.008 | 2.748 | 0.000 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.094 | 0.694 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.027 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 26.679 | 0.169 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.500 | 0.013 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.553 | 0.014 | 2.713 | 0.001 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 2.971 | 0.457 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.030 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 23.844 | 0.122 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.507 | 0.024 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.544 | 0.009 | 2.770 | 0.001 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 3.655 | 0.349 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.062 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.011 | 0.003 | 5.745 | 0.094 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans | fit | 0.027 | 0.029 | 10000 | 10000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.007 | 0.003 | 4.123 | 1.437 | See |
| 1 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.927 | 0.492 | See |
| 2 | KMeans | predict | 0.000 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.565 | 1.061 | See |
| 3 | KMeans | fit | 0.337 | 0.014 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 29.0 | NaN | 30.0 | NaN | 0.112 | 0.003 | 2.997 | 0.002 | See |
| 4 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.982 | 0.505 | See |
| 5 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.112 | 0.102 | See |
| 6 | KMeans | fit | 0.011 | 0.005 | 10000 | 10000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.006 | 0.001 | 1.870 | 0.240 | See |
| 7 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.054 | 0.568 | See |
| 8 | KMeans | predict | 0.000 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.089 | 0.569 | See |
| 9 | KMeans | fit | 0.135 | 0.005 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.049 | 0.002 | 2.769 | 0.002 | See |
| 10 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.126 | 0.535 | See |
| 11 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 0.995 | 0.092 | See |
| 12 | KMeans | fit | 0.157 | 0.006 | 10000 | 10000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.021 | 0.001 | 7.596 | 0.003 | See |
| 13 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.798 | 0.427 | See |
| 14 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.010 | 0.303 | See |
| 15 | KMeans | fit | 0.872 | 0.033 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 24.0 | NaN | 21.0 | NaN | 0.406 | 0.020 | 2.148 | 0.004 | See |
| 16 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.586 | 0.281 | See |
| 17 | KMeans | predict | 0.006 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.601 | 0.093 | See |
| 18 | KMeans | fit | 0.054 | 0.002 | 10000 | 10000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.019 | 0.001 | 2.889 | 0.006 | See |
| 19 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.907 | 0.598 | See |
| 20 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.099 | 0.243 | See |
| 21 | KMeans | fit | 0.271 | 0.046 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 22.0 | NaN | 24.0 | NaN | 0.187 | 0.026 | 1.449 | 0.049 | See |
| 22 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.907 | 0.311 | See |
| 23 | KMeans | predict | 0.006 | 0.002 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.678 | 0.160 | See |
| 24 | KMeans | fit | 0.673 | 0.011 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.486 | 0.018 | 1.386 | 0.002 | See |
| 25 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.010 | 0.585 | See |
| 26 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.823 | 0.426 | See |
| 27 | KMeans | fit | 30.948 | 0.000 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 9.826 | 0.065 | 3.150 | 0.000 | See |
| 28 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.556 | 0.582 | See |
| 29 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.239 | 0.133 | See |
| 30 | KMeans | fit | 0.583 | 0.010 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.441 | 0.022 | 1.323 | 0.003 | See |
| 31 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.959 | 0.631 | See |
| 32 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.176 | 0.619 | See |
| 33 | KMeans | fit | 12.807 | 0.097 | 1000000 | 1000000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.417 | 0.055 | 3.747 | 0.000 | See |
| 34 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.470 | 0.666 | See |
| 35 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.198 | 0.173 | See |
| 36 | KMeans | fit | 6.642 | 0.137 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.966 | 0.023 | 2.240 | 0.000 | See |
| 37 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.600 | 0.416 | See |
| 38 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.098 | 0.380 | See |
| 39 | KMeans | fit | 100.163 | 0.000 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 49.694 | 0.000 | 2.016 | 0.000 | See |
| 40 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.552 | 0.386 | See |
| 41 | KMeans | predict | 0.010 | 0.002 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 6.698 | 0.064 | See |
| 42 | KMeans | fit | 5.980 | 0.058 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.825 | 0.011 | 2.117 | 0.000 | See |
| 43 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.720 | 0.709 | See |
| 44 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.185 | 0.353 | See |
| 45 | KMeans | fit | 32.527 | 0.000 | 1000000 | 1000000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 21.906 | 0.024 | 1.485 | 0.000 | See |
| 46 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.808 | 0.407 | See |
| 47 | KMeans | predict | 0.010 | 0.001 | 1000000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 7.132 | 0.048 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.589 | 0.010 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 11.485 | 0.121 | 1.009 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.381 | 0.804 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 1.032 | 0.332 | See |
| 3 | LogisticRegression | fit | 0.790 | 0.017 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 0.792 | 0.030 | 0.997 | 0.002 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.001 | 0.071 | 1.421 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.001 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.004 | 0.001 | 0.566 | 0.105 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.038 | 0.002 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.022 | 0.003 | 1.714 | 0.016 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 1.368 | 1.107 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.796 | 0.467 | See |
| 3 | Ridge | fit | 0.008 | 0.001 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.003 | 0.000 | 3.020 | 0.036 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.628 | 1.126 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.868 | 0.411 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
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"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
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"dependencies_info": {
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